DocumentCode :
717389
Title :
Integration of outcome estimations with a clinical decision support system: Application in the neonatal intensive care unit (NICU)
Author :
Frize, Monique ; Gilchrist, Jeff ; Martirosyan, Hasmik ; Bariciak, Erika
Author_Institution :
Syst. & Comput. Eng. Dept., Carleton Univ., Ottawa, ON, Canada
fYear :
2015
fDate :
7-9 May 2015
Firstpage :
175
Lastpage :
179
Abstract :
Our previous research led to the development of mortality risk estimations for infants in the neonatal intensive care unit (NICU) using quality archived databases. A decision support system was created with a clinician module containing relevant patient information and a variety of outcome estimations; the PPADS (Physician-Parent Decision Support) tool also contains a module for parents with the aim to help them make joint decisions with physicians on the direction of care for their infant. New work developed the ANN-Builder which uses an open-source artificial neural network library that would enable handling real-time data streaming and automate the process of providing risk estimations of mortality. Additionally, the patient data and risk estimations were successfully integrated into the PPADS tool. The mortality estimations surpass the clinical expectations. The next and final step will be to replace missing values in the data and add alarms for major changes in the risk estimations provided by the system.
Keywords :
decision support systems; health care; neural nets; risk management; PPADS tool; clinical decision support system; clinician module; infant; mortality risk estimation; neonatal intensive care unit; open-source artificial neural network library; outcome estimation; patient information; physician-parent decision support; quality archived database; real-time data streaming; Artificial neural networks; Data models; Databases; Estimation; Pediatrics; Real-time systems; comparision of ANNs; decision-support; estimating mortality; integration systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Medical Measurements and Applications (MeMeA), 2015 IEEE International Symposium on
Conference_Location :
Turin
Type :
conf
DOI :
10.1109/MeMeA.2015.7145194
Filename :
7145194
Link To Document :
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